Among the major features of the new virtual application pattern in IBM Workload Deployer is the notion of elasticity. That is, as your application needs more resources, it gets them. When your application can meet its SLAs with fewer resources, the environment shrinks. With this kind of pattern, you enable elasticity by specifying a policy and defining the scaling trigger (i.e. CPU usage, application response times, database response times, etc.). What may have been a bit lost in some of these new announcements regarding IBM Workload Deployer is the fact that you can now leverage this core feature of cloud, elasticity, in your virtual system patterns.
If you have read this blog in the past, you probably already know that the Intelligent Management Pack is an option for virtual system patterns built using WebSphere Application Server Hypervisor Edition. When you enable the Intelligent Management Pack option, you are essentially building and deploying WebSphere Virtual Enterprise (WVE) environments. For those of you not familiar with WVE, the best way to describe it is that it provides you with application and application infrastructure virtualization capabilities. Of its many capabilities, one most germane to our discussion today is the ability for users to attach SLAs to applications and then have WVE automatically prioritize requests and manage resources in order to meet those SLAs. Inherent in this capability is the ability to dynamically start and stop application server processes (JVMs) as required. In other words, WVE provides JVM elasticity.
The fact that WVE provides JVM elasticity is nothing new. Further, IBM Workload Deployer started providing virtual machine (VM) elasticity in previous versions (when it was WebSphere CloudBurst). With this feature, you could add or remove VMs to an already deployed virtual system using dynamic virtual machine operations provided by the appliance. The catch was that the VM elasticity was a manual action and you could not link this elasticity to the same SLAs tied to your applications. Well, thanks to a new feature in WebSphere Virtual Enterprise and easy integration provided by the Intelligent Management Pack, this is no longer the case.
Starting in IBM Workload Deployer 3.0, you can take advantage of a new WVE feature called Elasticity Mode when using the Intelligent Management Pack. Elasticity mode is not unique to IBM Workload Deployer, but a concept new to the base WVE product. It allows one to define actions for how WVE should grow and shrink the set of nodes used by application server resources. Like the basic JVM elasticity capability in WVE, these node elasticity actions trigger based on SLAs tied to your applications. Consider the case that you are using elasticity mode and your application is not currently meetings its SLA. If WVE does not think it can start any more application server instances on the current set of nodes, it will grow the set of nodes per your elasticity configuration. Conversely, if WVE detects that it can meet SLAs with fewer nodes, it will shrink the resources per your elasticity configuration.
In IBM Workload Deployer, using elasticity mode becomes even easier. All you need to do is use the Intelligent Management Pack and enable the elasticity mode option in your virtual system patterns. When you do this, you get automatic integration between IBM Workload Deployer and the deployed WVE environment. What does that mean? It means that if WVE detects it needs more nodes, it will automatically call back into IBM Workload Deployer and request that the appliance provision a new VM that will serve as a node for application server processes. It also means that if WVE detects it could meet SLAs with fewer resources, it will call into IBM Workload Deployer and ask it to remove a node. All of this happens without any user scripting. All you have to do is enable this option in your patterns and configure SLAs appropriate for your applications.
To me, this exciting new feature brings out the best of elasticity capabilities in both IBM Workload Deployer and WebSphere Virtual Enterprise. The result is a single management plane that gives you both VM and JVM elasticity for your cloud-based application environments. Best of all, elasticity actions map directly to SLAs for your applications. After all, when it comes to cloud, it's the application that really matters!
I was very encouraged by the consistently positive response we got at IMPACT for our WebSphere CloudBurst and Rational Automation Framework for WebSphere (RAFW) integration. I believe there were many reasons for this response: accelerated time to value, decreased investment needs for activities that are not core to your business, lowered barrier of entry for provisioning and configuring WebSphere cells, and much more. While those are certainly all very real and valuable benefits, I also believe that quite a bit of interest in this integrated solution comes from the fact that it is applicable to a number of needs common to you, our WebSphere users.
With that in mind, let's look at some (not all) of the scenarios where WebSphere CloudBurst and RAFW integration can help you:
Create WebSphere CloudBurst patterns that include configuration without scripting: Users love our WebSphere CloudBurst patterns. They really see the value in codifying both the topology and configuration of their application infrastructure. However, some users do not have existing WebSphere configuration scripts and do not have the time and/or resource to invest in creating these scripts. They are looking for a solution that provides not only the provisioning of WebSphere environments but also the configuration of said environments (configuration beyond what our IBM Hypervisor Edition images encapsulate, specifically application-oriented configuration). RAFW provides this capability in the form of 500+ out-of-the-box configuration actions for WebSphere environments. This includes actions to create JDBC resources, create JMS queues, deploy applications, configure application containers, and much, much more. You can create WebSphere CloudBurst patterns that contain a special script package, which points back to a RAFW project containing a set of configuration actions. During deployment, WebSphere CloudBurst will provision your WebSphere environment and then cause the invocation of the specified RAFW project, which in turn runs a set of configuration actions against the provisioned environment. This means you can set up full-blown, ready-to-go application environments with absolutely no user-supplied scripting. In fact, I took this approach to setup a J2EE performance benchmark application, DayTrader 2.0, running on WebSphere Application Server. Those of you familiar with the application know this is not a trivial environment to stand up. Yet, I did it without having to personally write a single line of configuration scripting, and it was all ready to go in around thirty minutes.
Creating WebSphere CloudBurst patterns from existing environments: This comes up all the time. I go through a standard introduction to WebSphere CloudBurst, users see the value, love the patterns-based approach, and immediately want to know how they get their existing environments into the form of a pattern. RAFW, along with the special WebSphere CloudBurst script package, can make this a straightforward and hardened process. You use a capability in RAFW to import the configuration of an existing cell, thereby creating a RAFW environment for that configuration. You then create a WebSphere CloudBurst pattern with a topology congruent to your existing environment, attach the special script package I mentioned earlier, and you are done with the import! When you deploy this pattern, you simply specify the RAFW environment that you created earlier (the one that holds the configuration data for your existing environment) and a RAFW project that will apply the configuration data in that RAFW environment to the WebSphere environment provisioned by WebSphere CloudBurst. The creation of the WebSphere environment, as well as its configuration, happens in a completely automated fashion.
Configure, capture, reuse: There are many situations that may require you to make manual changes to a WebSphere cell after it has been deployed. For example, during performance testing for your application, you might discover that you need to tweak the number of available threads in the web container. As another example, for the first setup of a given application environment, you may want to quickly deploy the cell using WebSphere CloudBurst and then manually install and configure your applications to make sure everything is just right. In either case, it is likely that you want to capture the updated configuration and make sure that any future deployments use those updates. Again, WebSphere CloudBurst and RAFW makes this simple. First, you build a pattern that encapsulates your WebSphere topology (the types and quantity of nodes you want) and attach the special script package mentioned above. For the first deployment, you simply specify the name of the new RAFW environment you want to create. Once the system is up, you log into the WebSphere administration console, make your necessary customizations, and then you use RAFW to import that updated configuration thus updating the initially created RAFW environment. For subsequent deployments, you simply deploy the same pattern, specifying the same RAFW environment as well as a RAFW project, which RAFW automatically created for you during the first deployment. This project applies the configuration (the one you manually established and imported into RAFW) to the WebSphere environment setup by WebSphere CloudBurst.
Configure WebSphere environments across virtual and physical settings: It seems that in many cases our users manage the same WebSphere environment across both virtual and physical settings. For example, they may provision the application environment using WebSphere CloudBurst for everything from development to pre-production, and then for production provision that same environment to a set of physical servers. At least, they try to provision the same environment. In reality, it is tough to reproduce the exact same configuration once you break from the WebSphere CloudBurst patterns-based approach. However, if you stored the configuration of your WebSphere cell as a RAFW environment, you could apply that configuration data to a WebSphere cell regardless of whether it existed in the physical or virtual world. Once you move to physical, you do lose out on the fast provisioning, WebSphere intelligence, cloud management capabilities, and automated integration with RAFW that you get when using WebSphere CloudBurst, but if it is in your process to move to physical hardware at some point, reusing the same RAFW environment certainly eases the migration task.
I hope this sheds some light on some of the common issues WebSphere CloudBurst and the Rational Automation Framework for WebSphere can combine to solve really well. This is by no means an exhaustive list, but really meant to point out the broad application of the solution. If you want to see how it works, check out this video.
I’m going to take a different approach this week in the blog. Instead of me telling you about some of the features or uses of WebSphere CloudBurst, I thought I would catch up with someone using the product everyday, WebSphere Test Architect Robbie Minshall. Robbie is responsible for a team of testers that harness a lab of over 2,000 physical machines to put our WebSphere Application Server product through some pretty rigorous testing. Toward the beginning of this year Robbie’s team started to leverage the WebSphere CloudBurst Appliance in order to create the WebSphere Application Server environments needed for their testing.
Robbie, can you tell us a little bit about what the WebSphere Application Server test efforts entail?
In WebSphere Application Server development and test we have two primary scenarios. The first is making sure that developers have rapid access to code, test cases and server topologies so that they can write code, test cases and then execute test scenarios on meaningful topologies. The second scenario is an automated daily regression where in response to a build, we provision a massive amount of WebSphere Application Server topologies and execute our automated regression tests.
Previously we have supported these scenarios through the deployment of the Tivoli Provisioning Manager for operating system provisioning, some applications for checking out environments, and then a lot of automation scripts for the silent install and configuration of WebSphere Application Server cells.
Given those scenarios and the existing solution, what are your motivations for setting up a private cloud using WebSphere CloudBurst Appliance?
We are supporting these scenarios through a pretty complicated combination of technologies. These include silent WAS install scripts, wsadmin configuration scripts, a custom hardware leasing application and the utilization of Tivoli Provisioning Manager for OS Provisioning. This solution is working very well for us though as always we are looking for areas to improve, opportunities to simplify and to reduce our dependency on investment in our custom automation scripts. Mainly, there were 3 areas where we wanted to improve our framework: Availability, Utilization and Management. This is why we started looking to the WebSphere CloudBurst Appliance.
Can you expand a bit on what you are looking for in those three areas?
The first focus area we have is availability of environments. We really wanted to lower the entry requirement for the skills and education necessary to get a development or test environment. Setting up these environments has just been too hard, too time consuming, and too error prone. Using WebSphere CloudBurst we can provide an easy push button solution for developers to get on-demand access to the topologies they need.
The second area we are looking for significant improvements on is hardware utilization. Our budgets are tight and in our native automation pools we are only using between 6-12% of the available physical resources. In order to improve this we were looking at leveraging virtualization. WebSphere CloudBurst offers the classic benefit of virtualization with the nice additions of optimized WebSphere Application Server placement and really good topology and pattern management. In our initial experiments we were able to push the hardware utilization up to 90% of physical capacity and consistently were leveraging around 70% of our physical capacity.
Finally we are looking to improve and simplify our management of physical resources and automation. We work in a lot of small agile teams and organizational priorities change from iteration to iteration. Not only does WebSphere CloudBurst allow us to maintain a catalog of topologies or patterns for releases but it also allows us to adjust physical resource allocation to teams through the use of sub clouds or cloud groups.
Basically we felt that WebSphere CloudBurst would improve the availability of application environments, enhance automation, and improve hardware utilization all with very low physical and administrative costs.
What were some of the challenges involved with getting a cloud up and running in your test department?
One of our challenges seems like it would be common to many scenarios, especially in today’s world. Our budget for new hardware to build out our cloud infrastructure was initially very limited. Most cloud infrastructure designs depict very ideal hardware scenarios including SANs, large multicore machines, and private and public networks within a dedicated lab. Quite frankly we did not have the budget to create this from scratch. It was important for us to demonstrate value and data to warrant future investment in dedicated infrastructure. After some performance comparisons we were very happily surprised to see that we could leverage our existing mixed hardware within a distributed cloud. The performance of application environments dispensed by WebSphere CloudBurst on many small existing boxes in comparison to large multicore machines with a SAN was very comparable. This allows us to leverage existing hardware, with minimal investment all the while demonstrating the value and efficiencies of cloud computing. That data in turn has allowed us to obtain new dedicated hardware to iteratively build up a larger lab specifically for use with WebSphere CloudBurst.
Specifically with WebSphere CloudBurst, are there any tips/hints you would offer users getting started with the appliance?
Sure. First, we quickly realized as we added hypervisors to our WebSphere CloudBurst setup it was critical to have someone with network knowledge on hand. This is because the hypervisors came from various sections of our lab, and we really needed people with knowledge of how the network operated in those different sections. Once we had the right people we were able to setup WebSphere CloudBurst and deploy patterns within an hour and a half.
Moving forward we continued to have challenges as we dynamically moved systems between our native hardware pool and our cloud. Occasionally the WebSphere CloudBurst administrator would move a system into the cloud but incorrectly configure the network or storage information. This lead to some misconfigured hypervisors polluting our cloud. We overcame this, quite simply and satisfactorily I may add, by creating some simple WebSphere CloudBurst CLI scripts which add the hypervisors, test them individually, by carrying out a small deployment to that hypervisor, and then move the correctly configured hypervisors into the cloud after verifying success. Misconfigured hypervisors go into a pool for problem determination. This has allowed us to maintain a clean cloud, and we are able to dynamically move our hardware in and out of the cloud to meet our business objectives.
We also use the WebSphere CloudBurst CLI to prime the cloud so to speak. Before using a given hypervisor in our cloud, we execute scripts that ensure each unique virtual image in our catalog has been deployed to each of our hypervisors at least once. When the image is first deployed to a hypervisor, a cache is created on the hypervisor side of the connection, thus meaning subsequent deployments do not require the entire image to be transferred over the wire. This gives us consistent and fast deployment times once we are using a hypervisor in our cloud.
I would assume that like many applications deployed on WebSphere Application Server, your team’s applications have several external dependencies. Some of these dependencies won’t necessarily be in the cloud, so how did you handle this?
You’re right about the external dependencies. Our applications and test cases run on the WebSphere Application Server but are dependent upon many external resources such as databases, LDAP servers, external web services etc. WebSphere CloudBurst allows us to deploy WAS topologies in a very dynamic and configurable way but the 1.0.1 version does not allow us to deploy these external resources in the same manner. This was overcome by using script packages in our patterns. These script packages allow us to associate our test applications with various patterns we have defined. The script package definition also allows us to pass in parameters to the execution of our scripts. We supply these parameter values during deploy time, and these values are used to convey the name or location of various external resources. The scripts that install our applications can access these values and ensure the application is properly integrated with the set of resources not managed by the appliance.
What is your team looking to do next with WebSphere CloudBurst and their private cloud?
The next challenge on our plate is to keep up with the demand of our expanding cloud and to develop a more dynamic relationship between our native pools and our cloud using the Tivoli Provisioning Manager. These are fun challenges to have and we look forward to sharing our progress.
I'm glad I got to spend some time with Robbie to glean some insight into their work and progress with WebSphere CloudBurst. I hope this information was useful to you. It's always nice to hear about a product from practitioners who can give you hints, tips, gotchas, and other useful information. Be sure to let me know if you have any questions about what Robbie and his team are doing with WebSphere CloudBurst.
The reason I suggest the application proxy approach is twofold. First, it affords you the ability of having custom interactions with the REST API. For instance, you may insert logic into the server-side proxy code that returns only a subset of the JSON data contained in the response from the appliance. Alternatively, in an effort to reduce the chattiness on your client-side, you may join JSON data from multiple different REST requests to the appliance to fulfill a single client request. You may even decide to represent the data in an all together different format than JSON. All of these options and many more are available to you if you implement an application-based proxy to the REST API.
The second reason I suggest the application approach is that it is easier, and seemingly safer, to not deal with user passwords on the client-side. If you setup your application proxy, you can configure it to retrieve the appropriate password from a secure location (like an encoded file) based on information passed along in the request. This means the password information is only present in the request (in encoded form of course) from the application proxy to the WebSphere CloudBurst Appliance.
The good news about the application-based proxy approach is that it is simple to put in place. I composed one using the open source Apache Wink project. The Apache Wink project is an open source implementation of the JAX-RS specification (and then some), and it enables you to develop POJOs that are in turn exposed in a RESTful manner. In my case, I had a single resource POJO:
The Apache Wink runtime routes any HTTP GET request whose path is like /resources/* to the getResources method in the WCAResource class. This method passes along information taken from the query string (the host name of the target WebSphere CloudBurst Appliance and the requesting WebSphere CloudBurst username), as well as the HTTP path information and sends it on to the getResource method declared as follows:
The getResource method above uses the WebSphere CloudBurst host name and the request path to construct the URL for the corresponding WebSphere CloudBurst REST API call. Next, it constructs an Apache Wink Resource object and sends the REST request along to the WebSphere CloudBurst Appliance. How do we authenticate this request? We use the WebSphere CloudBurst username (sent as a query string parameter) to retrieve the appropriate encoded password information. Once we have that, we construct the necessary header for basic authorization over SSL.
The application-based proxy shown here is simply a pass-through. It does not manipulate the data returned from the WebSphere CloudBurst REST API, nor does it map a single client-side call to multiple REST requests. However, it would be simple enough to extend it to do any of those things. If you have any questions about the code here, please let me know. I'd be happy to share more of the code, or talk about how and where to extend it.
At the core of cloud computing discussions and cloud computing in general is the idea of virtualization. The word 'virtualization' might invoke different things depending on who you talk to but for cloud discussions many people think of virtual images: entire systems being stored even down to the operating systems. The advantages seem evident. Instead of complex deployment models you simply need to take an unused piece of hardware resource and lay in the exact pattern. The assumption is that the hardware is free an compatible but everything else is negotiable. I think, however that there are different levels of assumption within the cloud concept. Laying in entire systems from the OS up may be way more work than is necessary. The advantage is that there are fewer constraints on what kinds of things you can depoy in your cloud. But one of the big disadvantages are that there are fewer constraints on what kinds of things you can depoy in your cloud. Sometimes, productivity is higher when your developers are given the topology parameters and when he knows what resources are going to be available. In fact, the concept of cloud seems to infer that there are fewer assumptions needed so you will have maximum versatility. However, flexibility is an antagonist to stability and stability is needed for prodcutivity. In effect, more assumptions necessarily equals faster developement and quicker time to release. So is cloud the antithesis of productivity? No, of course not. The beauty of clouds is that you can have as many assumptions as you want. A productive cloud model could assume specific hardware, OS and even webservers and macro-topologies. The cloud's resources could simply be avalable platforms that serve as quickly added nodes that can be dynamically provisioned within an appserver deployment. I think cloud models can be stratfied based on the number of assumptions that are built into it. Level 0 clouds could be where the only assumtion is the that the physical machines will support the virtual images. Level 6 could be that virtual servers and resources can be cloned by template to act as expansion nodes to meet growing demand. Does this cross over into other scaling models? Yes. So what? It doesn't have to be unique in every aspect it merely has to be consistent for effective use.
A while back I co-authored an article along with Chris Ahl from Tivoli and Ken Klingensmith from WebSphere Technical Sales about the customization of virtual images in WebSphere CloudBurst. In the article we approached image customization as a means to enable IBM Tivoli Monitoring for the operating system within virtual machines dispensed by WebSphere CloudBurst. Today I posted a short demonstration that discusses and shows this particular integration scenario. If you are interested, but haven't had time to read the article, you may want to watch the video first as it should give you a good overview of the process and results.
Talk of Tivoli reminds me that IBM Pulse 2010 is just around the corner. I'll be going to discuss WebSphere CloudBurst and how it can be paired with software from IBM Tivoli for high-value integration scenarios. In the session I'll be talking about the Tivoli Monitoring integration as well as other key points such as our integration with Tivoli Service Automation Manager, IBM CloudBurst, and more. The best part about the session is that I will be co-presenting alongside a WebSphere CloudBurst customer that will dole out practical advice for using WebSphere CloudBurst within the enterprise. Join us on Tuesday February 23rd from 3:30 - 4:30 in Conference Center 306.
Remember, any time you have questions about WebSphere CloudBurst please pass them along. You can leave comments on this blog, or you can reach me at my new Twitter location @damrhein.
When IBM Workload Deployer v3.0 rolled around, the appliance introduced the concept of shared services. These were services that a cloud administrator could launch into the cloud infrastructure defined to IBM Workload Deployer, and use to serve a number of different application deployments. There were, and continue to be, two main shared services: a proxy service and a cache service. The shared proxy service does pretty much what you may guess. It provides request routing capabilities across multiple different instances of multiple different applications, thereby providing a centralized resource that encapsulates this basic need in an application environment. You can probably also guess what the caching service does. It caches things! Specifically, in IBM Workload Deployer v3.0 it provided in-memory caching of HTTP sessions, thus ensuring high availability of data stored in those sessions.
Undoubtedly, the ability to make HTTP session data fault tolerant is extremely critical in any application environment, cloud-based environments included. However, the applicability of a shared cache service is much further reaching, and in IBM Workload Deployer v3.1, we are starting to open this service up to your applications. What does this mean to you? Quite simply it now means that you can access this cache directly from your application code. If you are familiar with WebSphere eXtreme Scale or the DataPower XC10 Caching Appliance, then you know exactly what I mean. You can use the WebSphere eXtreme Scale ObjectGrid API to insert, read, update, and delete entries that exist in the in-memory cache. The underlying cache technology is based on the same code that powers WebSphere eXtreme Scale and DataPower XC10, so you can be sure that your cache is scalable, fault tolerant, responsive, and otherwise able to meet the needs of your application.
As I hope you find to be the case with many IBM Workload Deployer capabilities, this is a superbly simple capability to leverage. When you deploy virtual application patterns based on the IBM Workload Deployer Pattern for Web Applications, the capability is simply there. The underlying runtime that is serving your application is automatically augmented with the capabilities necessary so that your applications can connect to and utilize the deployed caching service. It is also worth pointing out that you can utilize the caching capabilities provided by this shared service for applications and application infrastructure that you deploy via virtual system patterns as well. You can either choose to augment the WebSphere Application Server environment with the XC10 Feature Pack (a deploy-time option for virtual system patterns built on WebSphere Application Server Hypervisor Edition v8), or you can configure WebSphere Application Server as you always would when integrating with a WebSphere eXtreme Scale environment or a DataPower XC10 Appliance.
What's the real benefit to all of this you ask? Well, when you use the shared caching service, you get the benefits of a distributed, in-memory, extremely scalable cache without having to deal with too much setup or administration. You simply tell IBM Workload Deployer how many resources you want to dedicate to your cache, and deploy the shared service. IBM Workload Deployer takes care of the details, including scaling in and out the cache to meet the needs of the system. On top of all of this, there is also an option to configure 'Next to the Cloud' caching. If you currently own DataPower XC10 appliances, you can make those available to virtual application pattern deployments (this was already possible with virtual system patterns) by simply providing details of the location of the appliance collective in question.
Put simply, setting up, administering, and utilizing an object caching service for your applications has never been easier. Check it out and let us know what you think!
If you are reading this blog then I am pretty sure that you are interested in the agility that can be achieved by rapidly provisioning middleware systems and standing up virtual applications in a private cloud environment. However there are other aspects of agility that you should also consider. One such aspect is the ability to build applications that can be easily maintained, updated, and extended. This is where OSGi technology comes into the picture.
If you have been working with the IBM Workload Deployer (or watching some IBM Workload Deployer demos) you may have noticed a category of components in the virtual application builder called OSGi Components.
Maybe you already know all about OSGi applications and the value they bring to an enterprise. Or, perhaps you noticed this and decided that you would search for some more information on this odd acronym and just what an OSGi application is all about.
In a nutshell OSGi technology is a way to define dynamic modules for Java. It provides a standard way to encapsulate components (called bundles) with metadata that define versioned package dependencies, service dependencies, packages exported, services exported, etc... basically everything you need to know about this bundle so that it can be connected up with other bundles to support a particular solution. These bundles can then be grouped together into applications and dynamically wired to fulfill necessary dependencies at runtime. The OSGi framework provides all of the necessary capability to manage the dependencies and resolve any problems.
Those who leverage OSGi technology benefit from improved time-to-market and reduced development costs. The loose coupling provided by the OSGi framework reduces maintenance costs and facilitates the dynamic delivery of components in a running system. Of course there's a lot more to it than just that ... involving portability across different environments, achieving the appropriate level of isolation or sharing within an environment, and integrating with the many different technologies and patterns already available today. I don't think I know enough about OSGi to do it justice here. But fortunately for me (and you) there are several experts who can make it all clear.
One such expert is Graham Charters and there is a great opportunity to hear him introduce this topic and also participate in a dialogue about the concepts and what they mean for your business. Graham will be leading a Global WebSphere Community Lab Chat on Wednesday of this week (July 20th) entitled: How can OSGi make your enterprise more agile. Graham is the IBM technical lead in the OSGi Alliance Enterprise Expert Group and an active participant in the open source community implementing many of these standards. So register now for this free session and learn how OSGi can make your enterprise even more agile.
In WebSphere CloudBurst, a script package is your vehicle to provide custom middleware configuration. This may mean installing applications, configuring application dependencies, or otherwise tuning the middleware layer. Script packages are essentially ZIP files that include some executable (shell script, wsadmin script, Java program, etc.), and optionally, artifacts that support the execution of the script. As was the intention, you can achieve just about anything you want with a script package. This allows you to be as flexible and creative as you need to be, but it can also leave you asking "Where do I start?" In this post, I want to take an in-depth look at constructing and using a script package in WebSphere CloudBurst.
Specifically, I want to create a script package that supplies configuration functionality for something I believe a fair number of you do: change the default ports used in WebSphere Application Server. To create this and deploy a pattern using the script package, I do the following:
Create a shell script that configures the desired ports
Add the new script as a WebSphere CloudBurst script package
Create a pattern with the new script package
Deploy the pattern and verify the result
First things first. I create the following shell script that configures the ports:
The script uses documented ANT commands included with the WebSphere Application Server to update the ports based on a starting port number. You will notice the script first sources the /etc/virtualimage.properties file. This file is automatically created by WebSphere CloudBurst on every virtual machine it starts. The file is a key/value file with basic information about the WebSphere cell such as the install root ($WAS_INSTALL_ROOT), the profile name ($PROFILE_NAME), host name ($HOSTNAME), and more. For a full list of the data that WebSphere CloudBurst includes in this file, check out this documentation.
In addition to utilizing the standard set of variables provided by WebSphere CloudBurst, my script above also makes use of the $STARTING_PORT variable. Obviously this variable is not in the standard set. In fact, I define the STARTING_POINT variable when I define my new script package in WebSphere CloudBurst.
First I zip up the shell script above and attach it to the new script package. Next, I tell WebSphere CloudBurst where to unzip the script package on the virtual machine, how to invoke the included script, and the name of any parameters to associate with the script. Once that is done I can use the script package in a new pattern.
For the sake of simplicity here, I create a new pattern by cloning an existing WebSphere Application Server single server pattern. I drag and drop the new Configure ports script package on the single part and end up with the pattern shown below.
Now I am ready to deploy the pattern by clicking the Deploy button. During the deployment process I configure each part in the pattern (in this there is only a single part). I supply configuration information like virtual memory allocation, WebSphere cell name, WebSphere node name, and password information. In addition, I also supply a value for the STARTING_PORT parameter that is part of the Configure ports script package included in the pattern. The value I supply here will get inserted into the /etc/virtualimage.properties file on the virtual machine, and the value's key will be STARTING_PORT.
Once the configuration information is supplied, I click OK on the configuration panel and deployment panel, and WebSphere CloudBurst goes about standing up my virtualized WebSphere cell and running my script to configure the ports for the server instance. When it is done, I login to the WebSphere Application Server administration console to verify my results. To do this, I navigate to the configuration for the single application server instance, and pull up its port definitions.
Based on the results I can see my customizations took effect. I successfully captured my own unique WebSphere environment (in this case with a custom port range) in the form of a pattern. This custom environment can be deployed as many times as I need, in an automated fashion, and I'm guaranteed consistent results each and every time.
I hope this gives you a better idea of what script packages are all about and how they can utilize both WebSphere CloudBurst and user-supplied data that exists in the /etc/virtualimage.properties file of each virtual machine. If you have any questions let me know. I'm on Twitter @damrhein, or you can leave a comment right here.
If you've read anything I've written about WebSphere CloudBurst up to this point you know all about patterns. Using the appliance you can easily and quickly build, deploy, and manage these representations of your middleware application environments. Today, I want to focus in on the deployment piece in particular and take a look at how you can easily automate this process.
You can use the WebSphere CloudBurst web console to deploy patterns, and when doing so you can even schedule the deployment to happen at a later date. This scheduling capability certainly gets you on the road to an automated deployment process, but what if you want to take it one step further and eliminate the need for someone to login and manually move around the web console to schedule automated deployments? In this case, you can use either the CLI or the REST interface that WebSphere CloudBurst offers.
In this post I thought I'd take a look at using the CLI interface in order to set the stage for some nice automation around pattern deployment. It starts out with a properties file that provides details about my deployment. This includes the cloud to deploy to, the pattern to deploy, password information, and the time at which the virtual system should start.
SYSTEM_NAME_PREFIX=New App Development
TARGET_CLOUD=Default ESX group
TARGET_PATTERN=WebSphere single server
Imagine that the properties file above gets written as the result of some other action, such as the completion of your application's build process. With the properties file in place, and I'll point out that your properties file can and probably will be more robust than above, let's move on to the code that handles the deployment process based on the information in said file. First, we have a small amount of CLI code to retrieve and parse the input data (I omitted the straight-forward properties retrieval for space):
from datetime import datetime, timedelta
from java.util import Properties
from java.io import FileInputStream
// read in and retrieve properties using java.util.Properties API (i.e. props.getProperty('DEPLOYMENT_DATE'))
parsedParts = deploymentDate.split(" ")
systemName = systemName + "_" + deploymentDate
dateParts = parsedParts.split("/")
timeParts = parsedParts.split(":")
monthPart = int(dateParts)
dayPart = int(dateParts)
yearPart = int(dateParts)
hourPart = int(timeParts)
minutePart = int(timeParts)
Next is the code that actually schedules the pattern deployment:
First we get the desired deployment time and current time as datetime objects. After that, assuming the desired deployment time has not already elapsed, we calculate the difference between the desired deployment time and current time. This difference, in seconds, is then added to the result of the time.time() value to come up with a start time. After that is done, we simply retrieve the cloud that was indicated in the properties file, and then we call the runInCloud method for the pattern indicated. When calling the runInCloud method we supply the name of the virtual system that will be created, password information, and the start time we calculated earlier. As a result of this method call, a task will be generated in the target WebSphere CloudBurst Appliance and the virtual system will be started at the specified time. This will happen in an automated fashion with no human intervention required.
That's really all there is to automating the pattern deployment process using the CLI. In a more complete, end-to-end scenario you may envision the completion of one process, such as an application build process mentioned above, result in the writing of the properties file and in turn the call into the CLI to deploy a pattern. As always, feel free to send me any comments or questions.